params_yaml
| task | mode | model | data | epochs | patience | batch | imgsz | save | save_period | cache | device | workers | project | name | exist_ok | pretrained | optimizer | verbose | seed | deterministic | single_cls | rect | cos_lr | close_mosaic | resume | amp | fraction | profile | overlap_mask | mask_ratio | dropout | val | split | save_json | save_hybrid | conf | iou | max_det | half | dnn | plots | source | show | save_txt | save_conf | save_crop | show_labels | show_conf | vid_stride | line_width | visualize | augment | agnostic_nms | classes | retina_masks | boxes | format | keras | optimize | int8 | dynamic | simplify | opset | workspace | nms | lr0 | lrf | momentum | weight_decay | warmup_epochs | warmup_momentum | warmup_bias_lr | box | cls | dfl | pose | kobj | label_smoothing | nbs | hsv_h | hsv_s | hsv_v | degrees | translate | scale | shear | perspective | flipud | fliplr | mosaic | mixup | copy_paste | cfg | tracker | save_dir |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| detect | train | yolov8n.pt | /workspaces/ultralytics/ultralytics/cfg/datasets/coco128.yaml | 15 | 50 | 16 | 640 | True | -1 | False | 8 | False | True | auto | True | 0 | True | False | False | False | 10 | False | True | 1 | False | True | 4 | 0 | True | val | False | False | 0.7 | 300 | False | False | True | False | False | False | False | True | True | 1 | False | False | False | False | True | torchscript | False | False | False | False | False | 4 | False | 0.01 | 0.01 | 0.937 | 0.0005 | 3 | 0.8 | 0 | 7.5 | 0.5 | 1.5 | 12 | 1 | 0 | 64 | 0.015 | 0.7 | 0.4 | 0 | 0.1 | 0.5 | 0 | 0 | 0 | 0.5 | 1 | 0 | 0 | botsort.yaml | /workspaces/ultralytics/runs/detect/train |
metrics_json
| train.box_loss | train.cls_loss | train.dfl_loss | metrics.precision(B) | metrics.recall(B) | metrics.mAP50(B) | metrics.mAP50-95(B) | val.box_loss | val.cls_loss | val.dfl_loss | lr.pg0 | lr.pg1 | lr.pg2 | model.parameters | model.GFLOPs | model.speed_PyTorch(ms) | step |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1.06434 | 1.05748 | 1.14749 | 0.73136 | 0.66376 | 0.72063 | 0.55248 | 0.9979 | 0.89099 | 1.06831 | 1.6898e-05 | 1.6898e-05 | 1.6898e-05 | 3157200 | 0 | 4.308 | 14 |
train/labels.jpg
train/train_batch0.jpg
train/train_batch1.jpg
train/train_batch2.jpg
train/train_batch40.jpg
train/train_batch41.jpg
train/train_batch42.jpg
val/val_batch0_labels.jpg
val/val_batch0_pred.jpg
val/val_batch1_labels.jpg
val/val_batch1_pred.jpg
val/val_batch2_labels.jpg
val/val_batch2_pred.jpg
val/F1_curve.png
val/PR_curve.png
val/P_curve.png
val/R_curve.png
val/confusion_matrix.png
val/confusion_matrix_normalized.png